For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

NOMA-Based Collaborative Beam Hopping Frequency Allocation Mechanism for Future LEO Satellite Systems

Low Earth orbit(LEO) satellite systems provide terrestrial users with services that are not limited by geographical location. However, the conflict between existing allocation schemes and the business variability between beams is becoming increasingly prominent. Beam hopping technology allows for a more flexible and versatile approach to satellite resource allocation. This paper proposes a beam hopping pattern optimization scheme that jointly considers the interference threshold distance and beam service priority, reducing the inter-beam co-channel interference(CCI). In the cluster area, a non-orthogonal multiple access(NOMA)-based collaborative beam hopping(NCBH) scheme is proposed to minimize the cell-edge user(CEU) interference. Since there is a difference in channel gain between the CEU and cellcenter user(CCU), this scheme forms a NOMA cluster to perform power domain multiplexing and formulates a NOMA cluster pairing strategy according to the user location to reduce the CCI of the CEU. After NOMA cluster pairing, the optimal carrier frequency of the NOMA cluster is selected by a reinforcement learning algorithm. The simulation results verify the excellent performance of the proposed NCBH scheme regarding the user’s received power, transmission rate, and outage probability.

High-Risk LEO Satellite Network Path Detection Based on Spatial and Temporal Delay Anomaly Analysis

The gradual deployment of Low-Earth Orbit(LEO)mega constellations with inter-satellite links(ISLs)promises ubiquitous,low-latency,and high-throughput satellite network services.However,networked LEO satellites with ISLs are also at risk of routing attacks such as hijacking.Existing defenses against route hijacking in terrestrial networks can hardly work for the LEO satellite network due to its high spatiotemporal dynamics.To deal with it,we propose RPD,a high-risk routing path detection method for LEO mega-constellation networks.RPD detects abnormal high-risk LEO network paths by checking the consistency between the path delay and the geographical distance.This is efficiently achieved by combining in-band measurements and out-of-band statistical processing to detect the anomaly of the clustering feature in the reference delay matrix.RPD avoids the recalculation of the header cryptographic marks when the handover occurs,thus greatly reducing the cost and improving the performance of highrisk path detection.Experiments showed that the proposed RPD mechanism achieves an average detection accuracy of 91.64%under normal network conditions,and maintain about 89%even when congestion occurs in multiple areas of the network and measurement noise is considered.In addition,RPD does not require any cryptographic operation on the intermediate node,only minimal communication cost with excellent scalability and deployability.

Challenges,Opportunities,and Future Research in the Integration of 5G/6G Networks,LEO Satellites,and IoT for Environmental Protection and Sustainable Development at ECSTAR

The rapid proliferation of connected IoT(Internet of Things)devices,along with the increasing demand for 5G mobile networks and ubiquitous high-speed connectivity,poses significant challenges in the telecommunications sector.To address these challenges,a comprehensive understanding of the integration of 5G/6G networks and LEO(Low Earth Orbit)satellite networks is required,forming the concept of“integrated networks”.Integration offers valuable advantages,including service continuity,wide-area coverage,and support for critical communications and emerging applications.This paper provides a high-level overview of the convergence of 5G/6G,LEO satellites,and IoT devices,shedding light on the technological challenges and standardization issues associated with the transition from 5G to 6G networks using NTNs(Non-Terrestrial Networks)based on LEO satellites.Furthermore,this research delves into the emerging social issues,potential possibilities,and the paradigm shift from the IoT to the IoI(Internet of Intelligence),which is poised to revolutionize the landscape of 6G wireless networks.By highlighting the interconnectedness of 5G/6G networks,LEO satellite systems,and IoT devices,it underscores the importance of leveraging these converging technologies to address environmental protection and achieve the United Nations SDGs(Sustainable Development Goals).In addition to providing valuable insights for readers seeking to comprehend the convergence of 5G/6G networks,LEO satellite systems,and IoT devices,this paper represents the outcomes of a comprehensive analysis conducted at the ECSTAR(Excellence Center of Space Technology and Research).Through an examination of technological challenges and advancements,it identifies future research directions and potential avenues for exploration at ECSTAR,thereby contributing to a broader understanding of integrated networks and their profound impact on future telecommunications systems.This research serves as a significant resource for advancing the knowledge and discourse surrounding the linkages between the convergence of these technologies,environmental protection,and the pursuit of the SDGs.

Resource allocation for uplink grant-free access in beam-hopping based LEO satellite systems

The low earth orbit(LEO) satellite system provides a promising solution for the global coverage of Internet of Things(IoT) services.Confronted with the sporadic uplink transmission from massive IoT terminals, this work investigates the grant-free access scheme and resource allocation algorithm for the beam-hopping(BH) based LEO satellite systems.To improve the packet success rate, the time slots are pre-allocated to each cell according to the number of terrestrial terminals and the probability of packet arrival.When the packets arrive, the terrestrial terminals perform contention-free or contention-based grant-free access with packet repetition in the time slots allocated to their cells.The analytical expression of the packet collision probability for the grant-free access scheme is derived to provide reference for the resource allocation.To reduce the computational complexity, a heuristic resource allocation algorithm is proposed to minimize the maximum cell packet collision probability in the system.Simulation results show that the proposed resource allocation scheme achieves lower packet collision probability and higher resource utilization ratio when compared with the uniform resource allocation scheme.

Reliability Evaluation of All-User Terminals in LEO Satellite Communication Network Based on Modular Reduction

LEO satellite communication network has a large number of satellites distributed in low orbits,which leads to multiple coverage of many areas on the ground.It is hard work to describe and evaluate the reliability of LEO satellite communication network.To solve this problem,the reliability of all-user terminals in LEO satellite communication network is defined,and the corresponding reliability evaluation method is proposed in the paper.Due to the large scale of the interstellar network,a modular reduction algorithm using the modular network instead of the original network for state decomposition is proposed in this paper.Case study shows that the calculation time of the proposed method is equivalent to 6.28%of the original state space decomposition algorithm.On this basis,the reliability of LEO satellite communication network is further analyzed.It is found that the reliability of LEO satellite network was more sensitive to the reliability of Inter-Satellite link and the satisfaction of global coverage in the early stage,and it is more sensitive to the reliability of the satellite in the later stage.The satellite-ground link has a relatively constant impact on of LEO satellite network.

A Safe and Reliable Routing Mechanism of LEO Satellite Based on SDN

Satellite networks have high requirements for security and data processing speed.In order to improve the reliability of the network,software-defined network(SDN)technology is introduced and a central controller is set in the network.Due to the characteristics of global perspective,control data separation,and centralized control of SDN,the idea of SDN is introduced to the design of the satellite network model.As a result,satellite nodes are only responsible for data transmission,while the maintenance of the links and the calculation of routes are implemented by the controller.For the massive LEO satellite network based on SDN,a state evaluation decision routing mechanism is proposed.The designed mechanism monitors the status of the entire network effectively and reduces the on-board load on the satellite network.The best routing decision is made under the comprehensive consideration of the current and historical status of each inter-satellite link between Low Earth Orbit(LEO)satellite network nodes.The calculation and storage requirements are controlled within a reasonable range.Based on the curve parameter transmission fuzzy encryption algorithm,a safe and reliable condition assessment decision routing mechanism(CADRM)is designed.It ensures that the personal information of the LEO satellite network can be transmitted safely and effectively.The experimental simulation results show the improvement of network throughput,the reduction of packet loss rate and the enhancing of network reliability.

A Fast and Accurate LEO Satellite-Based Direct Position Determination Assisted by TDOA Measurements

This paper focuses on the trusted vessel position acquisition using passive localization based on the booming low-earth-orbit(LEO) satellites. As the high signal-to-noise ratio(SNR) reception cannot always be guaranteed at LEO satellites, the recently developed direct position determination(DPD)is adopted. For LEO satellite-based passive localization systems, an efficient DPD is challenging due to the excessive exhaustive search range leading from broad satellite coverage. In order to reduce the computational complexity, we propose a time difference of arrival-assisted DPD(TA-DPD) which minimizes the searching area by the time difference of arrival measurements and their variances. In this way, the size of the searching area is determined by both geometrical constraints and qualities of received signals, and signals with higher SNRs can be positioned more efficiently as their searching areas are generally smaller.Both two-dimensional and three-dimensional passive localization simulations using the proposed TA-DPD are provided to demonstrate its efficiency and validity. The superior accuracy performance of the proposed method, especially at low SNRs conditions, is also verified through the comparison to conventional two-step methods. Providing a larger margin in link budget for satellite-based vessel location acquisition,the TA-DPD can be a competitive candidate for trusted marine location service.

LoS MIMO Transmission for LEO Satellite Communication Systems

To provide global service with low latency, the broadband low earth orbits (LEO) satellite constellation based communication systems have become one of the focuses in academic and industry. To allow for wideband access for user links, the feeder link of LEO satellite is correspondingly required to support high throughput data communications. To this end, we propose to apply line-of-sight (LoS) multiple-input multiple-output (MIMO) transmission for the feeder link to achieve spatial multiplexing by optimizing the antenna arrangement. Unlike the LoS MIMO applications for static scenarios, the movement of LEO satellites make it impractical to adjust the optimal antenna separation for all possible satellite positions. To address this issue, we propose to design the antenna placement to maximize the ergodic channel capacity during the visible region of the ground station. We first derive the closed-form probability distribution of the satellite trajectory in visible region. Based on which the ergodic channel capacity can be then calculated numerically. The antenna placement can be further optimized to maximize the ergodic channel capacity. Numerical results verify the derived probability distribution of the satellite trajectory, and show that the proposed LoS MIMO scheme can significantly increase the ergodic channel capacity compared with the existing SISO one.

OTFS Enabled NOMA for MMTC Systems over LEO Satellite

As a complement of terrestrial networks,non-terrestrial networks(NTN)have ad⁃vantages of wide-area coverage and service continuity.The NTN is potential to play an impor⁃tant role in the 5G new radio(NR)and beyond.To enable the massive machine type communi⁃cations(mMTC),the low earth orbit(LEO)satellite is preferred due to its lower transmission delay and path loss.However,the LEO satellite may generate notable Doppler shifts to de⁃grade the system performance.Recently,orthogonal time frequency space(OTFS)modulation has been proposed.It provides the opportunity to allocate delay Doppler(DD)domain resourc⁃es,which is promising for mitigating the effect of high mobility.Besides,as the LEO satellite constellation systems such as Starlink are thriving,the space spectrum resources have become increasingly scarce.Therefore,non-orthogonal multiple access(NOMA)is considered as a candidate technology to realize mMTC with limited spectrum resources.In this paper,the ap⁃plication of OTFS enabled NOMA for mMTC over the LEO satellite is investigated.The LEO satellite based mMTC system and the OTFS-NOMA schemes are described.Subsequently,the challenges of applying OTFS and NOMA into LEO satellite mMTC systems are discussed.Fi⁃nally,the potential technologies for the systems are investigated.

LDM-Satellite:A New Scheme for Packet Loss Classification over LEO Satellite Network

The packet loss classification has always been a hot and difficult issue in TCP congestion control research.Compared with the terrestrial network,the probability of packet loss in LEO satellite network increases dramatically.What’s more,the problem of concept drifting is also more serious,which greatly affects the accuracy of the loss classification model.In this paper,we propose a new loss classification scheme based on concept drift detection and hybrid integration learning for LEO satellite networks,named LDM-Satellite,which consists of three modules:concept drift detection,lost packet cache and hybrid integration classification.As far,this is the first paper to consider the influence of concept drift on the loss classification model in satellite networks.We also innovatively use multiple base classifiers and a naive Bayes classifier as the final hybrid classifier.And a new weight algorithm for these classifiers is given.In ns-2 simulation,LDM-Satellite has a better AUC(0.9885)than the single-model machine learning classification algorithms.The accuracy of loss classification even exceeds 98%,higher than traditional TCP protocols.Moreover,compared with the existing protocols used for satellite networks,LDM-Satellite not only improves the throughput rate but also has good fairness.

Orbital Elements Ephemerides and Interfaces Design of LEO Satellites

Low earth orbit satellites,with unique advantages,are prosperous types of navigation augmentation satellites for the GNSS satellites constellations.The broadcast ephemeris element needs to be designed as an important index of the augmented LEOs.The GPS ephemerides of 16/18 elements cannot be directly applied to the LEOs because of the poor fitting accuracies in along-track positional component.Besides,the ill-conditioned problem of the normal-matrix exists in fitting algorithm due to the small eccentricity of the LEO orbits.Based on the nonsingular orbital elements,5 sets of ephemerides with element numbers from 16 to 19 were designed respectively by adding or modifying orbital elements magnifying the along-track and radial positional components.The fitting experiments based on the LEO of 300 to 1500 km altitudes show that the fitting UREs of the proposed 16/17/18/18*/19-element ephemerides are better than 10/6/4/5/2.5 cm,respectively.According to the dynamical range of the fitting elements,the interfaces were designed for the 5 sets of ephemerides.The effects of data truncation on fitting UREs are at millimeter level.The total bits are 329/343/376/379/396,respectively.29/15 bits are saved for the 16/17-element ephemerides compared with the GPS16 ephemeris,while 64/61/41 bits can be saved for the 18/18*/19-element ephemerides compared with the GPS18 elements ephemeris.

Reinforcement learning based dynamic distributed routing scheme for mega LEO satellite networks

Recently,mega Low Earth Orbit(LEO)Satellite Network(LSN)systems have gained more and more attention due to low latency,broadband communications and global coverage for ground users.One of the primary challenges for LSN systems with inter-satellite links is the routing strategy calculation and maintenance,due to LSN constellation scale and dynamic network topology feature.In order to seek an efficient routing strategy,a Q-learning-based dynamic distributed Routing scheme for LSNs(QRLSN)is proposed in this paper.To achieve low end-toend delay and low network traffic overhead load in LSNs,QRLSN adopts a multi-objective optimization method to find the optimal next hop for forwarding data packets.Experimental results demonstrate that the proposed scheme can effectively discover the initial routing strategy and provide long-term Quality of Service(QoS)optimization during the routing maintenance process.In addition,comparison results demonstrate that QRLSN is superior to the virtual-topology-based shortest path routing algorithm.

Jamming-Aided Secure Communication in Ultra-Dense LEO Integrated Satellite-Terrestrial Networks

The ultra-dense low earth orbit(LEO)integrated satellite-terrestrial networks(UDLEO-ISTN)can bring lots of benefits in terms of wide coverage,high capacity,and strong robustness.Meanwhile,the broadcasting and open natures of satellite links also reveal many challenges for transmission security protection,especially for eavesdropping defence.How to efficiently take advantage of the LEO satellite’s density and ensure the secure communication by leveraging physical layer security with the cooperation of jammers deserves further investigation.To our knowledge,using satellites as jammers in UDLEO-ISTN is still a new problem since existing works mainly focused on this issue only from the aspect of terrestrial networks.To this end,we study in this paper the cooperative secrecy communication problem in UDLEOISTN by utilizing several satellites to send jamming signal to the eavesdroppers.An iterative scheme is proposed as our solution to maximize the system secrecy energy efficiency(SEE)via jointly optimizing transmit power allocation and user association.Extensive experiment results verify that our designed optimization scheme can significantly enhance the system SEE and achieve the optimal power allocation and user association strategies.

An IP mobility management scheme with dual location areas for IP/LEO satellite network

One of the issues of mobility management in a low Earth orbit (LEO) satellite network is the high-frequency location binding update initiated by mobile nodes (MNs).To solve this problem,we propose a location management scheme based on dual location area (LA) in an IP/LEO satellite network.The proposed scheme uses two kinds of LA,the fixed Earth station LA and satellite LA,to manage the location of the MNs together.MNs operate the binding update procedures only when they are moving out of both of the two LAs last registered.Geographical location information of MN is used in the binding update procedures,so that the network can page the idle MNs near their last registered location first,to enhance the probability of paging success.A detailed description of the implementation of the scheme is provided.Mathematical analysis shows that the proposed scheme reduces the location management cost and minimizes the influences of the distance between MN and its home agent.Paging cost is also reduced by introducing geographical location information in the binding update procedures.

Fairness based channel borrowing strategy in multimedia LEO satellite communications

A novel bandwidth allocation strategy along with a connection admission control technique was proposed to improve the utilization of network resources.It provides the network with better quality-of-service(QoS)guarantees,such as new call blocking probability(CBP)and handoff call drop-ping probability(CDP)in multimedia low earth orbit(LEO)satellite networks.Simulation results show that,compared with other bandwidth allocation schemes,the proposed scheme offers very low call dropping probability for real-time connections while,at the same time,keeping resource utilization high.Finally we discussed the fairness for the borrowed nonreal-time connections under three different channel borrowing methods.

Adaptive Tracking for Beam Alignment Between Ship-Borne Digital Phased-Array Antenna and LEO Satellite

In mobile satellite communication networks employing digital beam forming technology,beam alignment imposes great influence on link quality and network efficiency.Owing to complex coupling motion by low earth orbit(LEO)satellite and ship,direction of arrival(DOA)of target satellite varies rapidly and nonlinearly.It then causes difficulty to accurately track the DOA.In this work,an adaptive tracking algorithm is proposed by exploiting advantages of flexible parameter configuration of digital phased-array antenna.The alignment process basically consists of observation and tracking.In the observation stage,two-dimensional(2-D)multiple signal classification(MUSIC)is applied by the ship-borne digital phased-array antenna to estimate beam direction of satellite;in the tracking stage,an extended Kalman filter(EKF)based adaptive tracking is designed to achieve fast and accurate alignment.The proposed adaptive tracking improves performance by adaptively estimating tracking parameters in EKF firstly.The estimation results are then used as feedback to adaptively adjust digital phased-array antenna parameters to improve estimation accuracy of DOA.Simulation results under sea state 5 show that the proposed tracking algorithm improves tracking accuracy and stability over conventional ones.

Optimization of the Internet of Remote Things Data Acquisition Based on Satellite UAV Integrated Network

In order to achieve dependable and efficient data acquisition and transmission in the Internet of Remote Things(IoRT),we investigate the optimization scheme of IoRT data acquisition under the unmanned aerial vehicle(UAV)-low earth orbit(LEO)satellite integrated space-air-ground network,in which the UAV acquires data from massive Internet of Things(IoT)devices in special scenarios.To combine with the actual scenario,we consider two different data types,that is,delay-sensitive data and delay-tolerant data,the transmission mode is accordingly divided into two types.For delay-sensitive data,the data will be transmitted via the LEO satellite relay to the data center(DC)in real-time.For delay-tolerant data,the UAV will store and carry the data until the acquisition is completed,and then return to DC.Due to nonconvexity and complexity of the formulated problem,a multi-dimensional optimization Rate Demand based Joint Optimization(RDJO)algorithm is proposed.The algorithm first uses successive convex approximation(SCA)technology to solve the non-convexity,and then based on the block coordinate descent(BCD)method,the data acquisition efficiency is maximized by jointly optimizing UAV deployment,the bandwidth allocation of IoRT devices,and the transmission power of the UAV.Finally,the proposed RDJO algorithm is compared with the conventional algorithms.Simulation consequences demonstrate that the efficiency of IoRT data acquisition can be greatly improved by multi-parameter optimization of the bandwidth allocation,UAV deployment and the transmission power.

Load Balancing Routing Algorithm Based on Extended Link States in LEO Constellation Network

As an important part of satellite communication network,LEO satellite constellation network is one of the hot research directions.Since the nonuniform distribution of terrestrial services may cause inter-satellite link congestion,improving network load balancing performance has become one of the key issues that need to be solved for routing algorithms in LEO network.Therefore,by expanding the range of available paths and combining the congestion avoidance mechanism,a load balancing routing algorithm based on extended link states in LEO constellation network is proposed.Simulation results show that the algorithm achieves a balanced distribution of traffic load,reduces link congestion and packet loss rate,and improves throughput of LEO satellite network.